3,673 research outputs found
Market Model and Optimal Pricing Scheme of Big Data and Internet of Things (IoT)
Big data has been emerging as a new approach in utilizing large datasets to
optimize complex system operations. Big data is fueled with Internet-of-Things
(IoT) services that generate immense sensory data from numerous sensors and
devices. While most current research focus of big data is on machine learning
and resource management design, the economic modeling and analysis have been
largely overlooked. This paper thus investigates the big data market model and
optimal pricing scheme. We first study the utility of data from the data
science perspective, i.e., using the machine learning methods. We then
introduce the market model and develop an optimal pricing scheme afterward. The
case study shows clearly the suitability of the proposed data utility
functions. The numerical examples demonstrate that big data and IoT service
provider can achieve the maximum profit through the proposed market model
Profit Maximization Auction and Data Management in Big Data Markets
A big data service is any data-originated resource that is offered over the
Internet. The performance of a big data service depends on the data bought from
the data collectors. However, the problem of optimal pricing and data
allocation in big data services is not well-studied. In this paper, we propose
an auction-based big data market model. We first define the data cost and
utility based on the impact of data size on the performance of big data
analytics, e.g., machine learning algorithms. The big data services are
considered as digital goods and uniquely characterized with "unlimited supply"
compared to conventional goods which are limited. We therefore propose a
Bayesian profit maximization auction which is truthful, rational, and
computationally efficient. The optimal service price and data size are obtained
by solving the profit maximization auction. Finally, experimental results on a
real-world taxi trip dataset show that our big data market model and auction
mechanism effectively solve the profit maximization problem of the service
provider.Comment: 6 pages, 9 figures. This paper was accepted by IEEE WCNC conference
in Dec. 201
Privacy Management and Optimal Pricing in People-Centric Sensing
With the emerging sensing technologies such as mobile crowdsensing and
Internet of Things (IoT), people-centric data can be efficiently collected and
used for analytics and optimization purposes. This data is typically required
to develop and render people-centric services. In this paper, we address the
privacy implication, optimal pricing, and bundling of people-centric services.
We first define the inverse correlation between the service quality and privacy
level from data analytics perspectives. We then present the profit maximization
models of selling standalone, complementary, and substitute services.
Specifically, the closed-form solutions of the optimal privacy level and
subscription fee are derived to maximize the gross profit of service providers.
For interrelated people-centric services, we show that cooperation by service
bundling of complementary services is profitable compared to the separate sales
but detrimental for substitutes. We also show that the market value of a
service bundle is correlated with the degree of contingency between the
interrelated services. Finally, we incorporate the profit sharing models from
game theory for dividing the bundling profit among the cooperative service
providers.Comment: 16 page
Home Energy Management System and Internet of Things: Current Trends and Way Forward
Managing energy in the residential areas has becoming essential with the aim of cost saving, to realize a practical approach of home energy management system (HEMS) in the area of heterogeneous Internet-of-Thing (IoT) devices. The devices are currently developed in different standards and protocols. Integration of these devices in the same HEMS is an issue, and many systems were proposed to integrate them efficiently. However, implementing new systems will incur high capital cost. This work aims to conduct a review on recent HEMS studies towards achieving the same objectives: energy efficiency, energy saving, reduce energy cost, reduce peak to average ratio, and maximizing user's comfort. Potential research directions and discussion on current issues and challenges in HEMS implementation are also provided
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